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<title>JMeter Test Results Analysis</title>
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<h1>JMeter Test Results Analysis</h1>
<div class="section">
<h2>Summary</h2>
<table>
<tr><th>Metric</th><th>Value</th></tr>
<tr><td>Total Samples</td><td>24</td></tr>
<tr><td>Error Count</td><td>1</td></tr>
<tr><td>Error Rate</td><td>4.17%</td></tr>
<tr><td>Average Response Time</td><td>481.83 ms</td></tr>
<tr><td>Median Response Time</td><td>323.00 ms</td></tr>
<tr><td>90th Percentile</td><td>1015.00 ms</td></tr>
<tr><td>95th Percentile</td><td>1111.30 ms</td></tr>
<tr><td>99th Percentile</td><td>1208.47 ms</td></tr>
<tr><td>Min Response Time</td><td>156.00 ms</td></tr>
<tr><td>Max Response Time</td><td>1234.00 ms</td></tr>
<tr><td>Throughput</td><td>2.09 requests/second</td></tr>
<tr><td>Start Time</td><td>2024-12-03 19:50:00</td></tr>
<tr><td>End Time</td><td>2024-12-03 19:50:11.500000</td></tr>
<tr><td>Duration</td><td>11.50 seconds</td></tr>
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<h2>Endpoint Analysis</h2>
<table>
<tr>
<th>Endpoint</th>
<th>Samples</th>
<th>Errors</th>
<th>Error Rate</th>
<th>Avg Response Time</th>
<th>95th Percentile</th>
<th>Throughput</th>
</tr>
<tr>
<td>HomePage</td>
<td>8</td>
<td>0</td>
<td>0.00%</td>
<td>280.50 ms</td>
<td>413.30 ms</td>
<td>2.29 req/s</td>
</tr>
<tr>
<td>API_GetUser</td>
<td>6</td>
<td>0</td>
<td>0.00%</td>
<td>395.00 ms</td>
<td>553.25 ms</td>
<td>2.40 req/s</td>
</tr>
<tr>
<td>API_GetOrders</td>
<td>4</td>
<td>0</td>
<td>0.00%</td>
<td>208.75 ms</td>
<td>262.05 ms</td>
<td>2.67 req/s</td>
</tr>
<tr>
<td>API_Checkout</td>
<td>6</td>
<td>1</td>
<td>16.67%</td>
<td>1019.17 ms</td>
<td>1206.25 ms</td>
<td>2.40 req/s</td>
</tr>
</table>
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<h2>Bottleneck Analysis</h2>
<h3>Slow Endpoints</h3>
<table>
<tr>
<th>Endpoint</th>
<th>Response Time</th>
<th>Threshold</th>
<th>Severity</th>
</tr>
<tr>
<td>API_Checkout</td>
<td>1206.25 ms</td>
<td>713.78 ms</td>
<td class="severity-medium">MEDIUM</td>
</tr>
</table>
<h3>Error-Prone Endpoints</h3>
<table>
<tr>
<th>Endpoint</th>
<th>Error Rate</th>
<th>Threshold</th>
<th>Severity</th>
</tr>
<tr>
<td>API_Checkout</td>
<td>16.67%</td>
<td>1.00%</td>
<td class="severity-high">HIGH</td>
</tr>
</table>
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<h2>Insights and Recommendations</h2>
<h3>Recommendations</h3>
<table>
<tr>
<th>Priority</th>
<th>Issue</th>
<th>Recommendation</th>
<th>Expected Impact</th>
</tr>
<tr>
<td class="severity-high">HIGH</td>
<td>Moderate response time issues in endpoints: API_Checkout</td>
<td>Profile the code to identify bottlenecks and optimize the most expensive operations</td>
<td>Moderate improvement in response times</td>
</tr>
<tr>
<td class="severity-high">HIGH</td>
<td>High error rates in endpoints: API_Checkout</td>
<td>Investigate error logs, add proper error handling, and fix the root causes of errors</td>
<td>Significant reduction in error rates and improved reliability</td>
</tr>
<tr>
<td class="severity-high">HIGH</td>
<td>Server errors (1 occurrences)</td>
<td>Check server logs, fix application bugs, and add proper error handling</td>
<td>Reduction in server errors and improved reliability</td>
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</table>
<h3>Scaling Insights</h3>
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<tr>
<th>Topic</th>
<th>Description</th>
</tr>
<tr>
<td>No Correlation with Concurrency</td>
<td>There is little to no correlation between the number of concurrent users and response times, suggesting good scalability</td>
</tr>
<tr>
<td>No Performance Degradation Detected</td>
<td>No significant performance degradation was detected with increasing concurrent users within the tested range</td>
</tr>
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